The present invention relates generally to the remote configuration and observation of an imaging system over a network. More specifically, the present invention relates to a technique for dynamically adapting the image updates for a remote console observation based on network performance.
Medical institutions and facilities offer an increasingly wide range of services and procedures to address the needs of the patients. The services offered by the medical institutions, such as hospitals, clinics, and other medical facilities, may include medical imaging of the patients. A wide variety of medical imaging systems, such as x-ray system, computed tomography (CT) system, positron emission tomography (PET) system, electron beam tomography (EBT) system, magnetic resonance imaging (MRI) system, ultrasound system, tomosynthesis system, and so forth may be utilized in the medical facilities. The medical imaging systems may produce detailed images of a patient's internal tissues and organs, thereby mitigating the need for invasive exploratory procedures and providing valuable tools for identifying and diagnosing disease or for verifying wellness.
To provide support for the medical imaging systems, technicians and other support personnel may be utilized to train personnel on the operation of the medical imaging systems and/or to troubleshoot problems with the medical imaging systems. Though the number of these imaging systems has increased, the personnel qualified to service the imaging systems or assist in instructing new technicians in their use has not increased at the same rate. In addition, because the medical imaging systems may be geographically dispersed, the support of these imaging systems may be very costly. It may not be feasible for a technician to travel to each medical imaging system to provide the training and/or the troubleshooting needed.
To address the cost and support issues, the instructors and/or the technicians may remotely interact with the local operator workstation through a remote console observation to provide training and/or troubleshooting for the imaging system. The remote console observation may utilize a network that connects the local operator workstation at the imaging system with the remote operator workstation to provide the interaction between the systems. By utilizing the network for this interaction, travel time and costs associated with the servicing and training of personnel for the medical imaging systems may be reduced. For example, a remote service technician may access the imaging system to perform diagnostic routines, to configure imaging settings, or to train a local operator of the imaging system, while being located in a centralized service center.
Typically, updates of screen information may be transmitted to the local operator's workstation and the remote operator's workstation to display images from the imaging system. The remote operator and the local operator may also provide inputs, such as mouse movements or text, which are displayed on the respective workstations. However, the screen updates for the remote operator workstation are directly impacted by the performance of the network. For instance, as network congestion increases, the latency of the network may also increase. These network performance problems may delay the screen updates received at the remote operator workstation. As a result, the updates may be sporadic or slowed down based on the congestion or bandwidth problems being experienced on the network. The operator at the imaging system or the remote workstation may be unaware of the cause of the deterioration in the quality of the remote console observation. Accordingly, the network performance may hinder the interaction of the operators in the remote console observation.
To adjust for these conditions, the operator at the imaging system may have to manually adjust the screen capture rate or the amount of data being placed on the network. Because the network may be subject to various fluctuations, the operator at the imaging system may have to adjust the screen capture rate numerous times during a training session or while diagnosing or otherwise addressing a problem. With each time the system has to be manually adjusted, the portions of the imaging system may have to be restarted to incorporate the adjustments. Accordingly, the manual adjustment to account for network performance hinders the training or the diagnostics process. It is therefore desirable to allow remote servicing and training to be performed on a medical imaging system, which dynamically adapts the image updates for a remote operator workstation based on network performance, such as network congestion or latency.